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Wyse, Adam E.; McBride, James R. – Journal of Educational Measurement, 2021
A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch-based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the…
Descriptors: Item Response Theory, Computer Assisted Testing, Adaptive Testing, Test Items
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Kezer, Fatih – International Journal of Assessment Tools in Education, 2021
Item response theory provides various important advantages for exams carried out or to be carried out digitally. For computerized adaptive tests to be able to make valid and reliable predictions supported by IRT, good quality item pools should be used. This study examines how adaptive test applications vary in item pools which consist of items…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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Fuchimoto, Kazuma; Ishii, Takatoshi; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2022
Educational assessments often require uniform test forms, for which each test form has equivalent measurement accuracy but with a different set of items. For uniform test assembly, an important issue is the increase of the number of assembled uniform tests. Although many automatic uniform test assembly methods exist, the maximum clique algorithm…
Descriptors: Simulation, Efficiency, Test Items, Educational Assessment
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Jang, Jung Un; Kim, Eun Joo – Journal of Curriculum and Teaching, 2022
This study conducts the validity of the pen-and-paper and smart-device-based tests on optician's examination. The developed questions for each media were based on the national optician's simulation test. The subjects of this study were 60 students enrolled in E University. The data analysis was performed to verify the equivalence of the two…
Descriptors: Optometry, Licensing Examinations (Professions), Test Format, Test Validity
Anna Caroline Keefe – ProQuest LLC, 2022
Computer-assisted assessment continues to be incorporated into more and more mathematics courses. As this method of testing is used, questions are created to use through computer-assisted assessment. This study analyzed two types of questions used on computer-assisted assessment in Calculus I, II, and III courses. The first question type was…
Descriptors: Psychometrics, Computer Assisted Testing, Technology Integration, Calculus
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Paula Lehane; Darina Scully; Michael O'Leary – British Journal of Educational Technology, 2024
The use of animations and images in technology-based assessments (TBAs) represents a significant change in assessment design. To ensure that appropriate inferences can be drawn from assessments that use multimedia stimuli, their impact on test-taker performance and behaviour must be investigated. To achieve this, an experiment was conducted with…
Descriptors: Multimedia Materials, Animation, Computer Assisted Testing, Technology Uses in Education
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Matt I. Brown; Patrick R. Heck; Christopher F. Chabris – Journal of Autism and Developmental Disorders, 2024
The Social Shapes Test (SST) is a measure of social intelligence which does not use human faces or rely on extensive verbal ability. The SST has shown promising validity among adults without autism spectrum disorder (ASD), but it is uncertain whether it is suitable for adults with ASD. We find measurement invariance between adults with (n = 229)…
Descriptors: Interpersonal Competence, Autism Spectrum Disorders, Emotional Intelligence, Verbal Ability
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Marli Crabtree; Kenneth L. Thompson; Ellen M. Robertson – HAPS Educator, 2024
Research has suggested that changing one's answer on multiple-choice examinations is more likely to lead to positive academic outcomes. This study aimed to further understand the relationship between changing answer selections and item attributes, student performance, and time within a population of 158 first-year medical students enrolled in a…
Descriptors: Anatomy, Science Tests, Medical Students, Medical Education
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Zur, Amir; Applebaum, Isaac; Nardo, Jocelyn Elizabeth; DeWeese, Dory; Sundrani, Sameer; Salehi, Shima – International Educational Data Mining Society, 2023
Detailed learning objectives foster an effective and equitable learning environment by clarifying what instructors expect students to learn, rather than requiring students to use prior knowledge to infer these expectations. When questions are labeled with relevant learning goals, students understand which skills are tested by those questions.…
Descriptors: Equal Education, Prior Learning, Educational Objectives, Chemistry
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Ozsoy, Seyma Nur; Kilmen, Sevilay – International Journal of Assessment Tools in Education, 2023
In this study, Kernel test equating methods were compared under NEAT and NEC designs. In NEAT design, Kernel post-stratification and chain equating methods taking into account optimal and large bandwidths were compared. In the NEC design, gender and/or computer/tablet use was considered as a covariate, and Kernel test equating methods were…
Descriptors: Equated Scores, Testing, Test Items, Statistical Analysis
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C. H., Dhawaleswar Rao; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2023
Multiple-choice question (MCQ) plays a significant role in educational assessment. Automatic MCQ generation has been an active research area for years, and many systems have been developed for MCQ generation. Still, we could not find any system that generates accurate MCQs from school-level textbook contents that are useful in real examinations.…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Automation, Test Items
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
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Chen, Chia-Wen; Wang, Wen-Chung; Chiu, Ming Ming; Ro, Sage – Journal of Educational Measurement, 2020
The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Pugh, Debra; De Champlain, André; Gierl, Mark; Lai, Hollis; Touchie, Claire – Research and Practice in Technology Enhanced Learning, 2020
The purpose of this study was to compare the quality of multiple choice questions (MCQs) developed using automated item generation (AIG) versus traditional methods, as judged by a panel of experts. The quality of MCQs developed using two methods (i.e., AIG or traditional) was evaluated by a panel of content experts in a blinded study. Participants…
Descriptors: Computer Assisted Testing, Test Construction, Multiple Choice Tests, Test Items
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Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
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